Air pollution in cities_图文

Atmospheric Environment 33 (1999) 4029}4037

Air pollution in citiesHelmut MayerMeteorological Institute, University of Freiburg, D-79085 Freiburg, Germany

Abstract Air quality in cities is the result of a complex interaction between natural and anthropogenic environmental conditions. Air pollution in cities is a serious environmental problem } especially in the developing countries. The air pollution path of the urban atmosphere consists of emission and transmission of air pollutants resulting in the ambient air pollution. Each part of the path is in#uenced by di!erent factors. Emissions from motor tra$c are a very important source group throughout the world. During transmission, air pollutants are dispersed, diluted and subjected to photochemical reactions. Ambient air pollution shows temporal and spatial variability. As an example of the temporal variability of urban air pollutants caused by motor tra$c, typical average annual, weekly and diurnal cycles of NO, NO2, O and O are presented for an o$cial urban air-quality station in Stuttgart, southern Germany. They are supplemented V by weekly and diurnal cycles of selected percentile values of NO, NO2, and O3. Time series of these air pollutants give information on their trends. Results are discussed with regard to air pollution conditions in other cities. Possibilities for the assessment of air pollution in cities are shown. In addition, a qualitative overview of the air quality of the world's megacities is given. 1999 Elsevier Science Ltd. All rights reserved.Keywords: Emissions for urban air pollution; Cycles and trends of urban air pollutants; Assessment of air pollution

1. Introduction Most cities world-wide su!er from serious air-quality problems, which have received increasing attention in the past decade. A major probable reason for the air-quality problems is urban population growth, combined with change in land use due to increasing urban areas. The urban population growth is caused by (1) drift to the cities and (2) excess of births over deaths in the cities themselves } especially due to high birthrates in the developing countries. Mainly responsible for the migration to the cities is a deep structural change, especially in non-industrialised countries. This structural change is the consequence of (1) economic opening-up, (2) new trading partners, and (3) change of political conditions, e.g. democratisation. Structural change takes a rapid course in some countries, dubbed `tigersa. It is not surprising that the expected urban population growth from 1992 until 2010 is much higher for Lagos, Bombay or Dhaka than for Tokyo or New York (Table 1). Urban population growth has many consequences. One of them is higher emission of air pollutants. Even though for most air pollutants,

the emission rate per inhabitant is at present higher in industrialised countries, the tendency is obvious that this rate will in future be higher in the so-called developing countries. 2. Air pollution path in the atmosphere Emission of air pollutants is caused by di!erent anthropogenic processes which can be categorised into the source groups motor tra$c, industry, power plants, trade, and domestic fuel. In industrialised countries like Germany, emissions of `classica air pollutants are decreasing (Fig. 1). This trend is pronounced for carbon monoxide (CO), sulphur dioxide (SO) and total suspended particulate (TSP), and is weakly evident for nitrogen oxides (NOV) and non-methane volatile organic compounds (NMVOC). In Germany, emissions of CO and NOV caused by motor tra$c amount to more than half the total emissions of these pollutants, and NMVOC emissions of motor tra$c are just under half the total emission of NMVOC. Hence, it follows that motor vehicle tra$c seems to be the most important source group for air pollution,

especially in cities. The investigation by Mage et al. (1996) indicates that motor tra$c is a major source of air pollution in megacities (cities with a projected population of over 10 million by the year 2000). In half of them it is the single most important source. Since 1950, the global vehicle #eet has grown tenfold, and is estimated to double again within the next 20}30 years. Much of the

expected growth in vehicle numbers is likely to occur in developing countries and in eastern Europe. As cities expand, more people will drive more vehicles over greater distances and for longer time. Emissions of air pollutants by motor tra$c depends on di!erent factors such as tra$c density, driving habits or ratio of automobiles to trucks (Fig. 2). In contrast to the trend in the industrialised countries of decreasing emissions of air pollutants, emissions are presently increasing in some cities of non-industrialised countries (UNEP/WHO, 1993). Emitted air pollutants are dispersed and diluted in the atmosphere (Lyons and Scott, 1990). Chemical reactions producing, for example, photochemical ozone occur frequently during this transmission process (Alloway and Ayres, 1993; Bloom"eld et al., 1996). Dispersion and dilution of air pollutants are strongly in#uenced by meteorological conditions, especially by wind direction, wind speed, turbulence, and atmospheric stability. Topographical siting and urban structures like street canyons, for example, have a great e!ect on these meteorological parameters. Chemical reactions also depend on ambient weather conditions because they are in#uenced by shortwave radiation, air temperature, and air humidity. Along with chemical reactions, dispersion and dilution processes result in ambient air pollution which shows concentrations of di!erent substances varying with regard to time and space. Either measurements or modelling may be used to quantify these processes. `Classica air pollutants like SO , NO, NO and ozone (O ) are

long-term air pollution data from the o$cial urban airquality station `Stuttgart-Bad Cannstatta which is strongly in#uenced by motor tra$c. Stuttgart is a big city in southern Germany with about 500,000 residents.

3. Temporal variability of air pollutants Fig. 3 presents the average annual cycles of NO, NO , O and O at the station `Stuttgart-Bad Cannstatta in V the period 1981}1993. O is a measure of the O concenV tration contained in an air mass. It is de"ned as the sum of NO and O and is more suitable for the assessment of the photochemical O budget than O alone because it takes account of reversible chemical processes (Guicherit, 1988). The annual cycle of the primary air pollutant NO shows the greatest values at the end of November and January. The concentration of NO depends not only on emission, but also on weather conditions, which were very stable at that time. The average annual cycle of NO has the lowest values in summer (June and July) due to favourable atmospheric air mass exchange. In contrast to NO, the annual cycle of NO shows only slight vari ation, because this secondary substance is produced mainly by chemical reactions. O is an air pollutant that originates from di!erent sources (Heidorn and Yap, 1986). Ozone is partly produced in the lower troposphere by the action of short-wave radiation on anthropogenically released precursor substances. Therefore, the average annual cycle of O } as well as O } has the greatest values V in summer (July). The low O and O minimum in June is V a consequence of local weather conditions with increased cloudiness and less incoming short-wave radiation. The diurnal cycles of NO and NO (Fig. 4) have the shape of a double wave which is more pronounced for NO than for NO . Due to the tra$c density, the NO level is comparatively higher on weekdays than on weekends. This e!ect can also be seen for the secondary substance NO . The average diurnal variations on week days are greater for NO than for NO , because NO has a longer lifespan than the more reactive NO. The NO concentrations are noticeably higher in the morning than in the evening. This is because, in the morning, the rushhour is shorter and the atmosphere near the ground is more stable than in the evening. The low NO concentrations in the early afternoon result mainly from the reduction of O by NO. The diurnal cycles of O are typical for stations that are strongly in#uenced by motor tra$c. They show a distinct maximum in the afternoon caused by photochemical O formation and a comparatively low secondary maximum in the early morning which seems to be the result of downward transport of O from higher level containing more O . The secondary O maximum is more distinct the more the air quality station is

Fig. 2. Schematic illustration of the air pollution path in the atmosphere.

monitored routinely at most o$cial air-quality stations. `Speciala air pollutants like VOC, Pb, soot or other carcinogenic compounds are usually measured only during particular investigations over a limited period. Modelling of air pollutants enables the illustration of their spatial dispersion on di!erent urban scales (Williams et al., 1995), the forecasting of changes in air-quality conditions in#uenced by increasing built-up areas, new buildings such as skyscrapers, or industrial plants, and the forecasting of peak NO or O concentrations (Ziomas et al., 1995). The temporal variability of air pollutants can be generally characterised by time courses (annual, weekly, and diurnal cycles) and by trends. The spatial variability of air pollutants is pronounced if they are emitted or produced near the ground level, i.e. especially for emissions from motor tra$c. Hence it follows that the spatial variability of air pollutants primarily caused by motor tra$c is marked in cities, with their di!erent built-up and green spaces (Mayer and Haustein, 1994). This paper gives some basic information on the temporal variability of NO, NO , and O which are typical air pollutants from motor tra$c. The base is veri"ed

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Fig. 3. Average annual cycles of NO, NO , O and O at the urban air-quality station `Stuttgart-Bad Cannstatta for the period V 1981}1993.

Fig. 4. Average weekly and diurnal cycles of NO, NO , O and O at the urban air-quality station `Stuttgart-Bad Cannstatta for the V period 1981}1993.

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Fig. 5. Average weekly and diurnal cycle of percentile values of O at the urban air-quality station `Stuttgart-Bad Cannstatta for the period 1989}1993.

in#uenced by motor tra$c (Mayer and Schmidt, 1993). Thus, air a quality stations in green spaces in the suburbs or in the rural surroundings of cities do not show a secondary O maximum. Due to its de"nition, the diurnal cycle of O has no secondary maximum like V O . On weekends, the average O maximum values are a little higher than on weekdays, but this is not valid for O . However, O peak values (Fig. 5) } which V are most relevant for human health (Hall, 1996) } show a maximum mostly during weekdays (Mayer and Schmidt, 1993), which is the case for average O V values, too. From the analysis of NO and NO peak values (Mayer and Schmidt, 1994b), it becomes obvious that the highest values occur most frequently in the evening (Figs. 6 and 7), whereas the diurnal cycle of mean NO concentrations has its maximum in the morning. The patterns of temporal variability of air pollutants presented here can be found in cities world-wide (e.g.

Sluyter, 1996; Uno et al., 1996). Sometimes they are modi"ed by local circulations like sea breeze #ows (Nester, 1995) or short-time meteorological e!ects (Mayer and Schmidt, 1994a), but the basic structures are preserved. The level of air pollution is di!erent in di!erent cities. It depends on the background air pollution, speci"c emission conditions, general meteorological conditions and location of the air-quality station within the city (Kuttler, 1996).

4. Trends of air pollutants Time series of air pollutants indicate trends in air pollution. In cities of non-industrialised countries, time series of air pollutants are often too short for statistical trend analysis. In many cities of industrialised countries, however, air pollutant time series are su$ciently long to

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Fig. 6. Average weekly and diurnal cycle of percentile values of NO at the urban air-quality station `Stuttgart-Bad Cannstatta for the period 1989}1993.

permit trend analysis. As an example for a city in central Europe, Fig. 8 contains average monthly concentrations of NO, NO , O and O at the urban air-quality station V `Stuttgart-Bad Cannstatta. Trend analysis of these time series shows that NO and NO concentrations were tending to decrease slightly at `Stuttgart-Bad Cannstatta, whereas for O and O no V statistically signi"cant trend could be determined } indicating that O concentrations did not change during the investigation period. These results are typical of many cities in industrialised countries world-wide. Modi"cations are possible, if only selected seasons, speci"c urban structures or speci"c emission conditions are analysed (Uno et al., 1996; Wakamatsu et al., 1966. For example, Bezuglaya (1996) reports that emissions and concentrations of CO and NO have risen by more than 10% in the last ten years in selected cities in the Russian Federation, as a result of the increasing number of defective motor vehicles on urban motorways.

Seen on a global scale, there exist more and longer time series for SO , TSP and smoke than for air pollutants that are typical of motor tra$c. They show varying trends depending on substance, country features, station, location and general meteorological exchange conditions of the city (UNEP/WHO 1993).

5. Assessment of air pollution Exposure to elevated concentrations of ambient air pollutants causes adverse human health e!ects. A critical question in many urban environments is not whether the air in cities is unhealthy, but, given that air quality is poor, how severely is health a!ected (Hall, 1996). Answering this question is a di$cult task, because (1) assembling and analysing the air-quality data necessary for this problem is to a large degree location-speci"c and (2) appropriate indexes for the assessment of the air-quality

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Fig. 7. Average weekly and diurnal cycle of percentile values of NO at the urban air-quality station `Stuttgart-Bad Cannstatta for the period 1989}1993.

component of the urban climate have yet to be developed and rigorously tested. Nearly every country has standards to assess single air pollutants, e.g. EU-standards in Europe, NAAQS (National Ambient Air Quality Standards) in USA or WHO-AQGs (World Health Organization Air Quality Guidelines). But these standards are not su$cient, especially for urban air quality management or urban planning, because human beings in cities are exposed not to a single air pollutant alone, but to a mixture of di!erent substances. The problem is to develop an index based on air pollutants that are typical of di!erent emission source groups and for which data are easily available, i.e. they must be routinely recorded at o$cial air-quality stations. Meanwhile some indexes do exist for the assessment of the air pollution conditions in cities, e.g. Pollutant Standards Index PSI in USA or air quality stress index (LBI) in Germany (Mayer, 1993, 1996). One major challenge in

the development of an integral assessment index for air pollution in cities is to make it su$ciently relevant in environmental medical terms. On the other hand, if this index is too complicated, it is nearly impossible to use it in di!erent applied questions, e.g. in urban planning. This problem is currently under discussion with regard to LBI, which is an index for average and short-term air pollution loads and considers SO , NO and TSP, i.e. air pollutants from o$cial air-quality stations, for which data are easily available. The investigation on air pollution (SO , suspended particulate matter (SPM), lead (Pb), CO, NO and O ) in megacities by Mage et al. (1996) shows that air pollution is widespread across the megacities and is often most severe in cities in the developing countries. But even in others, health norms are exceeded, although to a smaller degree. Each of the 20 megacities has at least one major air pollutant which occurs at levels that exceed WHO

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Fig. 8. Average monthly concentrations of NO, NO , O and O at the urban air-quality station `Stuttgart-Bad Cannstatta for the V period 1981}1993.

health protection guidelines. Fourteen of these megacities have two such pollutants and seven (Beijing, Cairo, Jakarta, Los Angeles, Mexico City, Moscow and Sao Paulo) have three or more. The major problem a!ecting megacities as a group is their high level of SPM. It presents a very serious problem in 12 of the megacities surveyed by Mage et al. (1996), the majority of which are located in the Paci"c Basin. The concentrations of SPM in these cities are persistently above the WHO guidelines by a factor as much as two or three.

6. Conclusions Air quality in cities is getting worse as the population, tra$c, industrialisation and energy use increase. Urban air pollutants show typical annual, weekly and diurnal cycles. Some air pollutants are present in high concentrations, often above WHO guidelines, especially in cities of non-industrialised countries. Available time series of air pollutants in cities are often too short, especially in nonindustrialised countries, precluding meaningful statistical

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trend analysis of urban air pollutants. Where long-term trends can be calculated, they are decreasing for most `classica air pollutants other than O , especially in indus trialised countries. Time series of O show no statistically signi"cant trend in most cities world-wide. From a review of trends in air quality in di!erent cities made by Mage et al. (1996), it is quite evident that `history repeats itselfa. The experience of the current megacities in the developed countries is being repeated in the developing countries. Before rapid industrial development takes place, air pollution arises mainly from domestic sources and light industry. Concentrations of air pollutants are generally low and increase slowly as population increases. As industrial development and energy use grow, air pollution levels begin to rise rapidly. Then urban air pollution becomes a serious public health concern, and emission controls are introduced. Due to the complexity of the situation, an immediate improvement in air quality cannot usually be achieved. At best, the situation is stabilised, and serious air pollution persists for some time. Several megacities studied by Mage et al. (1996) are now in the state where additional controls must be implemented without delay. Experience has shown that the introduction of emission controls is followed by a staged reduction of air pollution as controls take e!ect. The earlier the integrated enforceable air-quality management plans are enacted, the lower the maximum pollution levels that will occur. This is important for those cities, especially in developing countries, that are not of the size and complexity of present-day megacities. Air-quality management should, therefore, be implemented in those cities where strategic planning is weak or non-existent, i.e. in half of all megacities. Due to the insu$ciency of air-quality information in many cities of the world, there is an immediate world-wide need to improve the monitoring and evaluation systems for urban air pollution.